Digital cameras tend to capture images with a high color depth—far higher than is typically needed in practice. For example, some cameras capture samples at a depth of 10 or even 12 bits per R, G and B channel, giving a total depth of 30 to 36 bits in RGB space.
The human eye on the other hand is usually not capable of distinguishing this many colors. From research into human vision, it has been estimated that a typical human can only perceive about 2 million different colors. That corresponds to a total color depth of about 20 bits (6 to 7 bits per channel).
If the captured data is to be encoded for transmission over a network, then high color depth information incurs a very high bitrate, as well as a high processing burden in the encoding. Similarly, if the data is to be encoded for storage then a high color depth incurs a lot of memory resource.
For this reason, raw image data captured from a camera is often quantized for the purpose of video encoding. This reduces the number of bits required to encode the video, for example reducing the bitrate required in a bitstream to be transmitted over a network, e.g. as part of a live video call such as a video VoIP (Voice over IP) call; or reducing the number of bits required to store the video in memory.